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Publication Index: WoSSubject: Regression

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    Software Code Smell Prediction Model Using Shannon, Renyi and Tsallis Entropies
    (MDPI, 2018) Blazauskas, Tomas; Gupta, Aakanshi; Misra, Sanjay; Suri, Bharti; Kumar, Vijay; Damasevicius, Robertas
    The current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality and reliability of software. Source code of the open source software is easily accessible by any developer, thus frequently modifiable. In this paper, we have proposed a mathematical model to predict the bad smells using the concept of entropy as defined by the Information Theory. Open-source software Apache Abdera is taken into consideration for calculating the bad smells. Bad smells are collected using a detection tool from sub components of the Apache Abdera project, and different measures of entropy (Shannon, Renyi and Tsallis entropy). By applying non-linear regression techniques, the bad smells that can arise in the future versions of software are predicted based on the observed bad smells and entropy measures. The proposed model has been validated using goodness of fit parameters (prediction error, bias, variation, and Root Mean Squared Prediction Error (RMSPE)). The values of model performance statistics (R-2, adjusted R-2, Mean Square Error (MSE) and standard error) also justify the proposed model. We have compared the results of the prediction model with the observed results on real data. The results of the model might be helpful for software development industries and future researchers.
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    Citation - WoS: 8
    Citation - Scopus: 10
    Employability of It Graduates From the Industry's Perspective: a Case Study in Turkey
    (Springer, 2013) Turhan, Cigdem; Akman, Ibrahim
    The qualifications that constitute the employability and identity of graduates are viewed differently by the academic community and the industry. Currently, it is observed for Information Technologies (IT) sector that the demands of the industry are not always satisfied by the perceived standards of the graduates. To provide feedback to the corresponding departments, a survey regarding employer expectations and factors affecting these expectations has been conducted among a number of senior professionals and managers working in the IT sector in Turkey regarding this inconsistency. The employer expectations are considered in two empirical categories as competencies and adequacies. The multiple regression analysis technique has been used to analyze the survey data. Based on the analysis, recommendations are provided to IT departments as well as their students to better fulfill the demands of the industry.